An analog-to-digital converter (ADC) is a circuit that samples and converts an analog signal to a digital signal. With respect to the allowable or meaningful signal values, an analog signal is continuous while a digital signal is discrete or quantized. Usually, the signals are represented by voltage levels, varying in a continuous fashion over some specified voltage range for analog signals and discrete specified quantized levels for digital signals. An important characteristic of an ADC is its resolution, which is a function of the number of quantized voltage levels to which the analog input signal may be assigned. Resolution thus describes the fineness of the quantization performed by the ADC. Generally, the higher the resolution of the ADC, the more accurate the digital representation of the analog signal will be. A high resolution ADC divides the input range into a larger number of subranges than a low resolution converter. Resolution is usually defined as the base 2 logarithm of the number of subranges the ADC input range has been divided into.
In most applications, it is either desired or required to have as high an ADC resolution as practical. However, increased resolution also increases the likelihood that the ADC output will not be a pure thermometer code. A thermometer code works similarly to a thermometer in that if comparator outputs in the ADC are listed in a column and ordered according to increasing reference values associated with the respective comparators that produced them, the level of a boundary between logic “1's” and logic “0's” would indicate the value of the analog input signal, much as a level of mercury in a mercury thermometer indicates the temperature. By way of example, a high resolution ADC may produce an output of 1101000, which deviates from a thermometer code by the third numeral from the left being 0 instead of 1. This may result from, for example, noise and offsets due to process, voltage, temperature, etc. being larger than the difference in adjacent reference levels between two comparators in the ADC, thus causing a comparator to make an incorrect decision. Consequently, the complexity of an encoder in an ADC system becomes prohibitive in terms of both the hardware required to encode the output of the ADC and the latency of the encoding computation. Furthermore, for each additional encoded bit of the digitized code, twice the number of comparators is needed, thereby increasing the power and/or area of the ADC, which is undesirable.
Conventionally, channel equalization, for example, decision feedback equalization (DFE) or feed-forward equalization (FFE), is sometimes used in communication systems to determine the correct bit sequence of the ADC output. To determine the correct bit value during a given bit period, equalization modifies the current sampled value by a function of the values determined during some number of previous or later-occurring bit periods. Unfortunately, if an incorrect decision is made during some bit period, the error will likely accumulate to cause more incorrect decisions.
An alternative technique to determine the proper bit sequence is to use a maximum likelihood (ML) detector, for example a Viterbi encoder. ML detectors determine the correct bit value during a given bit period by calculating the maximum likelihood of the bit value (for example, either logic “0” or logic “1”) based on the sampled value and the previous sequence of bits. ML detectors are disadvantageous primarily because they require substantial hardware to implement.
Signal degradation due to the channel or systems can sometimes be handled by the transmitting system. One common way a transmitting system does this is to use signal shaping techniques, such as, for example, pre-emphasizing high frequency components of the transmitted signal, vtx(t), or de-emphasizing low frequency components of vtx(t). Unfortunately, signal shaping techniques often add significant noise to the signal, which is undesirable. Even aggressive pre-emphasis may not be sufficient in many systems to permit the receiver to recover the proper bit sequence.
Accordingly, there exists a need for improved analog-to-digital conversion techniques which do not suffer from one or more of the above-described problems associated with conventional analog-to-digital conversion techniques.